Hierarchically integrating the production planning and scheduling to optimize the production planning process of a beverage compan

This research assesses the currently used production planning process of Vrumona, with the aim to
improve the process. As the trade-off between production- and inventory costs is not known,
Vrumona expects that the production planning process can be improved.
Currently, the production planning software Advanced Planning (AP) constructs the production plan.
The production plan is used by the production planner to construct the production schedule. AP uses
cost priorities and takes the constraints of the Syrup- and Packaging department into account to
construct the production plan. This production planning approach does not use the internally
available inventory capacity as a restriction, making this planning approach not account for higher
inventory costs when soft drinks need to be stored externally. The constructed production plans
cannot fulfil the customer demand. Therefore, the production planner modifies the production plans,
with the aim to meet the customer demand.
The purpose of this research is to structurally improve the production planning approach and
minimize the total production- and inventory costs, while maintaining the current service level of
99.5%. For this research we define the following research question:
How can Vrumona structurally improve their production planning approach to minimize the
production- and inventory costs, while maintaining a customer service level of 99.5%?
This research focuses on two of the nine production lines. Production line 4 is selected, as this
production line has limited available production capacity. Production line 10 is selected, as this
production line has excessive production capacity. Production line 4 bottles 20cl glass bottles for the
Out of Home industry and production line 10 bottles 1.5 litre cartons for the Retail industry. With
these production lines, we can show how the planning approaches perform for both types of
production capacities.
To show how the production planning process can be improved, this research developed three
planning approaches for the production planning process of the Supply Chain Planning department.
The research compares these planning approaches with the currently used planning approach AP.
The planning approaches focus on the tactical production planning problem. In order to compare
these approaches, it is important to define how much changeover time the constructed production
plans use. Therefore, we optimize the production sequence per production week of the production
plans with a scheduling algorithm (SA) that uses sequence dependent changeover times. One of the developed planning approaches uses the algorithm of AP software, and uses real
changeover- and inventory costs rather than the currently used cost priorities. The other two
planning approaches use an Integrated Production Planning and Scheduling (IPPS) approach to
construct a production plan. These IPPS approaches take product families into account, which make
the approaches willing to combine soft drinks of the same product family in the same production
week. This provides a better approximation of used changeover time in a week. Moreover, these
planning approaches take into account the internal inventory capacity level, which defines when soft
drinks need to be stored externally for higher storage costs. In addition, these planning approaches
can extend the available production capacity, resulting in higher costs. The research compares the
following four planning approaches: Current (AP/SA): Software Advanced Planning (AP)
The current planning approach uses the Advanced Planning software, which uses cost priorities.
Alternative 1 (MILP/SA): Mixed Integer Linear Programming (MILP) approach
This planning approach uses the mathematical optimisation technique that attempts to construct
a production plan within the defined constraints with the lowest costs.
Alternative 2 (AS/SA): Adaptive Search (AS) and Simulated Annealing (SA) approach
This planning approach constructs an initial production plan (AS), where the lot-sizes are
computed with the Economic Production Quantity (EPQ). The Simulated Annealing (SA) algorithm
optimizes the initial production plan to lower the total costs.
Alternative 3 (AP/SA real costs): Software Advanced Planning (AP) with actual costs
This planning approach uses AP, but uses actual changeover- and inventory
costs instead of the currently used cost priorities.